Overview

Dataset statistics

Number of variables56
Number of observations15120
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.5 MiB
Average record size in memory448.0 B

Variable types

BOOL44
NUM12

Warnings

Soil_Type7 has constant value "15120" Constant
Soil_Type15 has constant value "15120" Constant
Id has unique values Unique
Horizontal_Distance_To_Hydrology has 1590 (10.5%) zeros Zeros
Vertical_Distance_To_Hydrology has 1890 (12.5%) zeros Zeros

Reproduction

Analysis started2021-01-08 21:32:45.178160
Analysis finished2021-01-08 21:33:49.046230
Duration1 minute and 3.87 seconds
Software versionpandas-profiling v2.9.0
Download configurationconfig.yaml

Variables

Id
Real number (ℝ≥0)

UNIQUE

Distinct15120
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7560.5
Minimum1
Maximum15120
Zeros0
Zeros (%)0.0%
Memory size118.2 KiB
2021-01-08T16:33:49.188231image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile756.95
Q13780.75
median7560.5
Q311340.25
95-th percentile14364.05
Maximum15120
Range15119
Interquartile range (IQR)7559.5

Descriptive statistics

Standard deviation4364.91237
Coefficient of variation (CV)0.5773311779
Kurtosis-1.2
Mean7560.5
Median Absolute Deviation (MAD)3780
Skewness0
Sum114314760
Variance19052460
MonotocityStrictly increasing
2021-01-08T16:33:49.364290image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
20471< 0.1%
 
67581< 0.1%
 
149781< 0.1%
 
88331< 0.1%
 
108801< 0.1%
 
47271< 0.1%
 
67741< 0.1%
 
6291< 0.1%
 
26761< 0.1%
 
129151< 0.1%
 
149621< 0.1%
 
88171< 0.1%
 
108641< 0.1%
 
47111< 0.1%
 
6131< 0.1%
 
26921< 0.1%
 
26601< 0.1%
 
128991< 0.1%
 
149461< 0.1%
 
88011< 0.1%
 
108481< 0.1%
 
46951< 0.1%
 
67421< 0.1%
 
5971< 0.1%
 
26441< 0.1%
 
Other values (15095)1509599.8%
 
ValueCountFrequency (%) 
11< 0.1%
 
21< 0.1%
 
31< 0.1%
 
41< 0.1%
 
51< 0.1%
 
61< 0.1%
 
71< 0.1%
 
81< 0.1%
 
91< 0.1%
 
101< 0.1%
 
ValueCountFrequency (%) 
151201< 0.1%
 
151191< 0.1%
 
151181< 0.1%
 
151171< 0.1%
 
151161< 0.1%
 
151151< 0.1%
 
151141< 0.1%
 
151131< 0.1%
 
151121< 0.1%
 
151111< 0.1%
 

Elevation
Real number (ℝ≥0)

Distinct1665
Distinct (%)11.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2749.322553
Minimum1863
Maximum3849
Zeros0
Zeros (%)0.0%
Memory size118.2 KiB
2021-01-08T16:33:49.580309image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum1863
5-th percentile2117
Q12376
median2752
Q33104
95-th percentile3397
Maximum3849
Range1986
Interquartile range (IQR)728

Descriptive statistics

Standard deviation417.6781873
Coefficient of variation (CV)0.151920402
Kurtosis-1.082115791
Mean2749.322553
Median Absolute Deviation (MAD)367
Skewness0.07563970694
Sum41569757
Variance174455.0682
MonotocityNot monotonic
2021-01-08T16:33:49.768347image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
2290250.2%
 
2830250.2%
 
3371240.2%
 
3244230.2%
 
2820230.2%
 
2955230.2%
 
2795230.2%
 
2952230.2%
 
2962220.1%
 
2304220.1%
 
2809220.1%
 
2978220.1%
 
2413220.1%
 
2707220.1%
 
2850220.1%
 
2763220.1%
 
2289210.1%
 
2739210.1%
 
2827210.1%
 
2784210.1%
 
2807210.1%
 
2328210.1%
 
2311200.1%
 
3256200.1%
 
2751200.1%
 
Other values (1640)1456996.4%
 
ValueCountFrequency (%) 
18631< 0.1%
 
18741< 0.1%
 
18791< 0.1%
 
18881< 0.1%
 
18892< 0.1%
 
18961< 0.1%
 
18981< 0.1%
 
18991< 0.1%
 
19011< 0.1%
 
19032< 0.1%
 
ValueCountFrequency (%) 
38492< 0.1%
 
38481< 0.1%
 
38462< 0.1%
 
38441< 0.1%
 
38421< 0.1%
 
38391< 0.1%
 
38361< 0.1%
 
38311< 0.1%
 
38271< 0.1%
 
38252< 0.1%
 

Aspect
Real number (ℝ≥0)

Distinct361
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean156.6766534
Minimum0
Maximum360
Zeros110
Zeros (%)0.7%
Memory size118.2 KiB
2021-01-08T16:33:49.974340image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile13
Q165
median126
Q3261
95-th percentile344
Maximum360
Range360
Interquartile range (IQR)196

Descriptive statistics

Standard deviation110.0858014
Coefficient of variation (CV)0.7026305386
Kurtosis-1.150244484
Mean156.6766534
Median Absolute Deviation (MAD)77
Skewness0.450935294
Sum2368951
Variance12118.88367
MonotocityNot monotonic
2021-01-08T16:33:50.166339image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
451170.8%
 
01100.7%
 
901090.7%
 
63890.6%
 
76870.6%
 
27820.5%
 
315810.5%
 
75800.5%
 
108790.5%
 
117780.5%
 
34770.5%
 
72770.5%
 
121770.5%
 
135750.5%
 
80750.5%
 
57750.5%
 
53740.5%
 
62730.5%
 
124710.5%
 
86710.5%
 
61710.5%
 
111700.5%
 
18700.5%
 
84700.5%
 
52690.5%
 
Other values (336)1311386.7%
 
ValueCountFrequency (%) 
01100.7%
 
1480.3%
 
2500.3%
 
3540.4%
 
4510.3%
 
5460.3%
 
6570.4%
 
7480.3%
 
8560.4%
 
9510.3%
 
ValueCountFrequency (%) 
3602< 0.1%
 
359330.2%
 
358470.3%
 
357580.4%
 
356500.3%
 
355450.3%
 
354510.3%
 
353550.4%
 
352600.4%
 
351550.4%
 

Slope
Real number (ℝ≥0)

Distinct52
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16.5015873
Minimum0
Maximum52
Zeros5
Zeros (%)< 0.1%
Memory size118.2 KiB
2021-01-08T16:33:50.394880image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile5
Q110
median15
Q322
95-th percentile32
Maximum52
Range52
Interquartile range (IQR)12

Descriptive statistics

Standard deviation8.453926762
Coefficient of variation (CV)0.5123099134
Kurtosis-0.2383101358
Mean16.5015873
Median Absolute Deviation (MAD)6
Skewness0.5236583383
Sum249504
Variance71.4688777
MonotocityNot monotonic
2021-01-08T16:33:50.611877image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
117404.9%
 
107394.9%
 
137174.7%
 
146994.6%
 
126774.5%
 
96644.4%
 
156644.4%
 
166404.2%
 
175984.0%
 
85743.8%
 
75733.8%
 
185583.7%
 
205523.7%
 
195193.4%
 
214653.1%
 
64653.1%
 
224583.0%
 
234503.0%
 
54232.8%
 
243942.6%
 
253592.4%
 
263292.2%
 
283132.1%
 
43052.0%
 
272972.0%
 
Other values (27)194812.9%
 
ValueCountFrequency (%) 
05< 0.1%
 
1780.5%
 
21340.9%
 
32101.4%
 
43052.0%
 
54232.8%
 
64653.1%
 
75733.8%
 
85743.8%
 
96644.4%
 
ValueCountFrequency (%) 
521< 0.1%
 
501< 0.1%
 
495< 0.1%
 
481< 0.1%
 
473< 0.1%
 
46150.1%
 
453< 0.1%
 
445< 0.1%
 
432< 0.1%
 
423< 0.1%
 

Horizontal_Distance_To_Hydrology
Real number (ℝ≥0)

ZEROS

Distinct400
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean227.1957011
Minimum0
Maximum1343
Zeros1590
Zeros (%)10.5%
Memory size118.2 KiB
2021-01-08T16:33:50.804448image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q167
median180
Q3330
95-th percentile631
Maximum1343
Range1343
Interquartile range (IQR)263

Descriptive statistics

Standard deviation210.0752957
Coefficient of variation (CV)0.9246446774
Kurtosis2.803984388
Mean227.1957011
Median Absolute Deviation (MAD)120
Skewness1.488052491
Sum3435199
Variance44131.62986
MonotocityNot monotonic
2021-01-08T16:33:51.028030image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0159010.5%
 
3012078.0%
 
1504973.3%
 
604903.2%
 
424523.0%
 
674112.7%
 
853812.5%
 
1083612.4%
 
902841.9%
 
1202831.9%
 
952591.7%
 
1342551.7%
 
1242471.6%
 
2122121.4%
 
2771881.2%
 
2421881.2%
 
1621881.2%
 
1901851.2%
 
1751831.2%
 
1801741.2%
 
2011671.1%
 
1271661.1%
 
2101601.1%
 
1921601.1%
 
2281571.0%
 
Other values (375)627541.5%
 
ValueCountFrequency (%) 
0159010.5%
 
3012078.0%
 
424523.0%
 
604903.2%
 
674112.7%
 
853812.5%
 
902841.9%
 
952591.7%
 
1083612.4%
 
1202831.9%
 
ValueCountFrequency (%) 
13431< 0.1%
 
13181< 0.1%
 
12941< 0.1%
 
12612< 0.1%
 
12602< 0.1%
 
12181< 0.1%
 
12131< 0.1%
 
12081< 0.1%
 
12031< 0.1%
 
12011< 0.1%
 

Vertical_Distance_To_Hydrology
Real number (ℝ)

ZEROS

Distinct423
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean51.07652116
Minimum-146
Maximum554
Zeros1890
Zeros (%)12.5%
Memory size118.2 KiB
2021-01-08T16:33:51.276027image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum-146
5-th percentile-4
Q15
median32
Q379
95-th percentile176
Maximum554
Range700
Interquartile range (IQR)74

Descriptive statistics

Standard deviation61.23940613
Coefficient of variation (CV)1.198973711
Kurtosis3.403498704
Mean51.07652116
Median Absolute Deviation (MAD)32
Skewness1.53777568
Sum772277
Variance3750.264863
MonotocityNot monotonic
2021-01-08T16:33:51.452029image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0189012.5%
 
52171.4%
 
32061.4%
 
42001.3%
 
81981.3%
 
71821.2%
 
101761.2%
 
91661.1%
 
21651.1%
 
61621.1%
 
111591.1%
 
121591.1%
 
131581.0%
 
221400.9%
 
141400.9%
 
11390.9%
 
201350.9%
 
231330.9%
 
161320.9%
 
171260.8%
 
191260.8%
 
211250.8%
 
-11230.8%
 
251220.8%
 
181210.8%
 
Other values (398)952063.0%
 
ValueCountFrequency (%) 
-1461< 0.1%
 
-1341< 0.1%
 
-1231< 0.1%
 
-1151< 0.1%
 
-1141< 0.1%
 
-1101< 0.1%
 
-1081< 0.1%
 
-1041< 0.1%
 
-1031< 0.1%
 
-1002< 0.1%
 
ValueCountFrequency (%) 
5541< 0.1%
 
5472< 0.1%
 
4111< 0.1%
 
4031< 0.1%
 
4011< 0.1%
 
3972< 0.1%
 
3951< 0.1%
 
3931< 0.1%
 
3901< 0.1%
 
3871< 0.1%
 

Horizontal_Distance_To_Roadways
Real number (ℝ≥0)

Distinct3250
Distinct (%)21.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1714.023214
Minimum0
Maximum6890
Zeros3
Zeros (%)< 0.1%
Memory size118.2 KiB
2021-01-08T16:33:51.659638image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile242
Q1764
median1316
Q32270
95-th percentile4635.1
Maximum6890
Range6890
Interquartile range (IQR)1506

Descriptive statistics

Standard deviation1325.066358
Coefficient of variation (CV)0.7730737525
Kurtosis1.022419366
Mean1714.023214
Median Absolute Deviation (MAD)690
Skewness1.247810678
Sum25916031
Variance1755800.854
MonotocityNot monotonic
2021-01-08T16:33:51.848639image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
150880.6%
 
120560.4%
 
390470.3%
 
618450.3%
 
1110430.3%
 
700410.3%
 
108380.3%
 
1273370.2%
 
900370.2%
 
212370.2%
 
335370.2%
 
990370.2%
 
242360.2%
 
607360.2%
 
361350.2%
 
1082350.2%
 
228340.2%
 
750340.2%
 
277340.2%
 
450340.2%
 
1050340.2%
 
1020340.2%
 
960330.2%
 
1167330.2%
 
1140330.2%
 
Other values (3225)1413293.5%
 
ValueCountFrequency (%) 
03< 0.1%
 
30150.1%
 
425< 0.1%
 
60110.1%
 
67130.1%
 
85100.1%
 
90230.2%
 
95190.1%
 
108380.3%
 
120560.4%
 
ValueCountFrequency (%) 
68901< 0.1%
 
68361< 0.1%
 
68111< 0.1%
 
67661< 0.1%
 
66791< 0.1%
 
66601< 0.1%
 
65082< 0.1%
 
64141< 0.1%
 
64061< 0.1%
 
63711< 0.1%
 

Hillshade_9am
Real number (ℝ≥0)

Distinct176
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean212.7042989
Minimum0
Maximum254
Zeros1
Zeros (%)< 0.1%
Memory size118.2 KiB
2021-01-08T16:33:52.071626image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile151
Q1196
median220
Q3235
95-th percentile250
Maximum254
Range254
Interquartile range (IQR)39

Descriptive statistics

Standard deviation30.56128689
Coefficient of variation (CV)0.143679686
Kurtosis1.218810484
Mean212.7042989
Median Absolute Deviation (MAD)18
Skewness-1.093680561
Sum3216089
Variance933.9922561
MonotocityNot monotonic
2021-01-08T16:33:52.278622image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
2262791.8%
 
2292691.8%
 
2242651.8%
 
2282611.7%
 
2302601.7%
 
2332481.6%
 
2232451.6%
 
2192421.6%
 
2312391.6%
 
2252361.6%
 
2322341.5%
 
2212311.5%
 
2352281.5%
 
2362251.5%
 
2222231.5%
 
2272221.5%
 
2342221.5%
 
2382201.5%
 
2392181.4%
 
2422131.4%
 
2202121.4%
 
2372071.4%
 
2412011.3%
 
2182011.3%
 
2452011.3%
 
Other values (151)931861.6%
 
ValueCountFrequency (%) 
01< 0.1%
 
581< 0.1%
 
592< 0.1%
 
651< 0.1%
 
731< 0.1%
 
781< 0.1%
 
802< 0.1%
 
811< 0.1%
 
833< 0.1%
 
852< 0.1%
 
ValueCountFrequency (%) 
2541901.3%
 
2532001.3%
 
2521891.2%
 
2511741.2%
 
2501921.3%
 
2491951.3%
 
2481781.2%
 
2471881.2%
 
2461811.2%
 
2452011.3%
 

Hillshade_Noon
Real number (ℝ≥0)

Distinct141
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean218.9656085
Minimum99
Maximum254
Zeros0
Zeros (%)0.0%
Memory size118.2 KiB
2021-01-08T16:33:52.464660image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum99
5-th percentile175
Q1207
median223
Q3235
95-th percentile250
Maximum254
Range155
Interquartile range (IQR)28

Descriptive statistics

Standard deviation22.80196554
Coefficient of variation (CV)0.1041349174
Kurtosis1.153484179
Mean218.9656085
Median Absolute Deviation (MAD)14
Skewness-0.9532317075
Sum3310760
Variance519.9296327
MonotocityNot monotonic
2021-01-08T16:33:52.687657image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
2253272.2%
 
2293242.1%
 
2263202.1%
 
2243132.1%
 
2303112.1%
 
2233032.0%
 
2322982.0%
 
2222972.0%
 
2282941.9%
 
2182931.9%
 
2212921.9%
 
2272891.9%
 
2312841.9%
 
2202721.8%
 
2362701.8%
 
2342691.8%
 
2162661.8%
 
2142631.7%
 
2332611.7%
 
2152551.7%
 
2112511.7%
 
2192471.6%
 
2172471.6%
 
2352321.5%
 
2442281.5%
 
Other values (116)811453.7%
 
ValueCountFrequency (%) 
994< 0.1%
 
1021< 0.1%
 
1031< 0.1%
 
1071< 0.1%
 
1112< 0.1%
 
1133< 0.1%
 
1141< 0.1%
 
1151< 0.1%
 
1161< 0.1%
 
1181< 0.1%
 
ValueCountFrequency (%) 
2541330.9%
 
2531631.1%
 
2521521.0%
 
2511831.2%
 
2501671.1%
 
2491761.2%
 
2481961.3%
 
2472101.4%
 
2462141.4%
 
2452071.4%
 

Hillshade_3pm
Real number (ℝ≥0)

Distinct247
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean135.0919974
Minimum0
Maximum248
Zeros88
Zeros (%)0.6%
Memory size118.2 KiB
2021-01-08T16:33:53.007262image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile53
Q1106
median138
Q3167
95-th percentile207
Maximum248
Range248
Interquartile range (IQR)61

Descriptive statistics

Standard deviation45.89518871
Coefficient of variation (CV)0.3397328458
Kurtosis-0.08734390755
Mean135.0919974
Median Absolute Deviation (MAD)30
Skewness-0.3408272326
Sum2042591
Variance2106.368347
MonotocityNot monotonic
2021-01-08T16:33:53.221263image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
1431821.2%
 
1491611.1%
 
1321561.0%
 
1331541.0%
 
1421541.0%
 
1361541.0%
 
1371521.0%
 
1381481.0%
 
1541481.0%
 
1521451.0%
 
1501441.0%
 
1571410.9%
 
1511390.9%
 
1351380.9%
 
1481380.9%
 
1441370.9%
 
1151360.9%
 
1561360.9%
 
1631350.9%
 
1241340.9%
 
1301330.9%
 
1181330.9%
 
1311320.9%
 
1291320.9%
 
1211300.9%
 
Other values (222)1152876.2%
 
ValueCountFrequency (%) 
0880.6%
 
11< 0.1%
 
33< 0.1%
 
41< 0.1%
 
62< 0.1%
 
71< 0.1%
 
81< 0.1%
 
92< 0.1%
 
103< 0.1%
 
112< 0.1%
 
ValueCountFrequency (%) 
2482< 0.1%
 
2474< 0.1%
 
2464< 0.1%
 
2454< 0.1%
 
2443< 0.1%
 
2434< 0.1%
 
2423< 0.1%
 
2413< 0.1%
 
2407< 0.1%
 
2395< 0.1%
 
Distinct2710
Distinct (%)17.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1511.147288
Minimum0
Maximum6993
Zeros2
Zeros (%)< 0.1%
Memory size118.2 KiB
2021-01-08T16:33:53.413800image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile296.9
Q1730
median1256
Q31988.25
95-th percentile3663.05
Maximum6993
Range6993
Interquartile range (IQR)1258.25

Descriptive statistics

Standard deviation1099.936493
Coefficient of variation (CV)0.7278817235
Kurtosis3.385415788
Mean1511.147288
Median Absolute Deviation (MAD)595
Skewness1.617098874
Sum22848547
Variance1209860.288
MonotocityNot monotonic
2021-01-08T16:33:53.594344image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
618650.4%
 
541510.3%
 
636450.3%
 
607430.3%
 
573420.3%
 
960420.3%
 
752410.3%
 
942400.3%
 
342400.3%
 
242400.3%
 
277390.3%
 
977390.3%
 
212380.3%
 
524370.2%
 
700370.2%
 
335370.2%
 
902370.2%
 
726360.2%
 
484360.2%
 
408360.2%
 
997350.2%
 
391350.2%
 
808350.2%
 
671340.2%
 
912340.2%
 
Other values (2685)1412693.4%
 
ValueCountFrequency (%) 
02< 0.1%
 
3090.1%
 
42110.1%
 
60100.1%
 
67200.1%
 
8580.1%
 
9090.1%
 
95190.1%
 
108250.2%
 
12080.1%
 
ValueCountFrequency (%) 
69931< 0.1%
 
68531< 0.1%
 
67231< 0.1%
 
66861< 0.1%
 
66611< 0.1%
 
66321< 0.1%
 
66151< 0.1%
 
66061< 0.1%
 
66001< 0.1%
 
65971< 0.1%
 
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.2 KiB
0
11523 
1
3597 
ValueCountFrequency (%) 
01152376.2%
 
1359723.8%
 
2021-01-08T16:33:53.765342image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.2 KiB
0
14621 
1
 
499
ValueCountFrequency (%) 
01462196.7%
 
14993.3%
 
2021-01-08T16:33:53.831348image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.2 KiB
0
8771 
1
6349 
ValueCountFrequency (%) 
0877158.0%
 
1634942.0%
 
2021-01-08T16:33:53.898458image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.2 KiB
0
10445 
1
4675 
ValueCountFrequency (%) 
01044569.1%
 
1467530.9%
 
2021-01-08T16:33:53.967457image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Soil_Type1
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.2 KiB
0
14765 
1
 
355
ValueCountFrequency (%) 
01476597.7%
 
13552.3%
 
2021-01-08T16:33:54.031457image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Soil_Type2
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.2 KiB
0
14497 
1
 
623
ValueCountFrequency (%) 
01449795.9%
 
16234.1%
 
2021-01-08T16:33:54.093457image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Soil_Type3
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.2 KiB
0
14158 
1
 
962
ValueCountFrequency (%) 
01415893.6%
 
19626.4%
 
2021-01-08T16:33:54.160454image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Soil_Type4
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.2 KiB
0
14277 
1
 
843
ValueCountFrequency (%) 
01427794.4%
 
18435.6%
 
2021-01-08T16:33:54.230454image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Soil_Type5
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.2 KiB
0
14955 
1
 
165
ValueCountFrequency (%) 
01495598.9%
 
11651.1%
 
2021-01-08T16:33:54.306501image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Soil_Type6
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.2 KiB
0
14470 
1
 
650
ValueCountFrequency (%) 
01447095.7%
 
16504.3%
 
2021-01-08T16:33:54.376526image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Soil_Type7
Boolean

CONSTANT
REJECTED

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.2 KiB
0
15120 
ValueCountFrequency (%) 
015120100.0%
 
2021-01-08T16:33:54.442502image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Soil_Type8
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.2 KiB
0
15119 
1
 
1
ValueCountFrequency (%) 
015119> 99.9%
 
11< 0.1%
 
2021-01-08T16:33:54.499503image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Soil_Type9
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.2 KiB
0
15110 
1
 
10
ValueCountFrequency (%) 
01511099.9%
 
1100.1%
 
2021-01-08T16:33:54.865501image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.2 KiB
0
12978 
1
2142 
ValueCountFrequency (%) 
01297885.8%
 
1214214.2%
 
2021-01-08T16:33:54.935503image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.2 KiB
0
14714 
1
 
406
ValueCountFrequency (%) 
01471497.3%
 
14062.7%
 
2021-01-08T16:33:54.994500image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.2 KiB
0
14893 
1
 
227
ValueCountFrequency (%) 
01489398.5%
 
12271.5%
 
2021-01-08T16:33:55.062507image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.2 KiB
0
14644 
1
 
476
ValueCountFrequency (%) 
01464496.9%
 
14763.1%
 
2021-01-08T16:33:55.128504image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.2 KiB
0
14951 
1
 
169
ValueCountFrequency (%) 
01495198.9%
 
11691.1%
 
2021-01-08T16:33:55.201113image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Soil_Type15
Boolean

CONSTANT
REJECTED

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.2 KiB
0
15120 
ValueCountFrequency (%) 
015120100.0%
 
2021-01-08T16:33:55.283104image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.2 KiB
0
15006 
1
 
114
ValueCountFrequency (%) 
01500699.2%
 
11140.8%
 
2021-01-08T16:33:55.327102image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.2 KiB
0
14508 
1
 
612
ValueCountFrequency (%) 
01450896.0%
 
16124.0%
 
2021-01-08T16:33:55.394103image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.2 KiB
0
15060 
1
 
60
ValueCountFrequency (%) 
01506099.6%
 
1600.4%
 
2021-01-08T16:33:55.459620image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.2 KiB
0
15074 
1
 
46
ValueCountFrequency (%) 
01507499.7%
 
1460.3%
 
2021-01-08T16:33:55.524617image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.2 KiB
0
14981 
1
 
139
ValueCountFrequency (%) 
01498199.1%
 
11390.9%
 
2021-01-08T16:33:55.604209image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.2 KiB
0
15104 
1
 
16
ValueCountFrequency (%) 
01510499.9%
 
1160.1%
 
2021-01-08T16:33:55.673739image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.2 KiB
0
14775 
1
 
345
ValueCountFrequency (%) 
01477597.7%
 
13452.3%
 
2021-01-08T16:33:55.746740image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.2 KiB
0
14363 
1
 
757
ValueCountFrequency (%) 
01436395.0%
 
17575.0%
 
2021-01-08T16:33:55.810738image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.2 KiB
0
14863 
1
 
257
ValueCountFrequency (%) 
01486398.3%
 
12571.7%
 
2021-01-08T16:33:55.902736image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.2 KiB
0
15119 
1
 
1
ValueCountFrequency (%) 
015119> 99.9%
 
11< 0.1%
 
2021-01-08T16:33:55.964738image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.2 KiB
0
15066 
1
 
54
ValueCountFrequency (%) 
01506699.6%
 
1540.4%
 
2021-01-08T16:33:56.031839image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.2 KiB
0
15105 
1
 
15
ValueCountFrequency (%) 
01510599.9%
 
1150.1%
 
2021-01-08T16:33:56.100883image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.2 KiB
0
15111 
1
 
9
ValueCountFrequency (%) 
01511199.9%
 
190.1%
 
2021-01-08T16:33:56.164219image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.2 KiB
0
13829 
1
 
1291
ValueCountFrequency (%) 
01382991.5%
 
112918.5%
 
2021-01-08T16:33:56.235225image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.2 KiB
0
14395 
1
 
725
ValueCountFrequency (%) 
01439595.2%
 
17254.8%
 
2021-01-08T16:33:56.297219image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.2 KiB
0
14788 
1
 
332
ValueCountFrequency (%) 
01478897.8%
 
13322.2%
 
2021-01-08T16:33:56.376950image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.2 KiB
0
14430 
1
 
690
ValueCountFrequency (%) 
01443095.4%
 
16904.6%
 
2021-01-08T16:33:56.455951image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.2 KiB
0
14504 
1
 
616
ValueCountFrequency (%) 
01450495.9%
 
16164.1%
 
2021-01-08T16:33:56.522950image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.2 KiB
0
15098 
1
 
22
ValueCountFrequency (%) 
01509899.9%
 
1220.1%
 
2021-01-08T16:33:56.609013image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.2 KiB
0
15018 
1
 
102
ValueCountFrequency (%) 
01501899.3%
 
11020.7%
 
2021-01-08T16:33:56.672017image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.2 KiB
0
15110 
1
 
10
ValueCountFrequency (%) 
01511099.9%
 
1100.1%
 
2021-01-08T16:33:56.734044image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.2 KiB
0
15086 
1
 
34
ValueCountFrequency (%) 
01508699.8%
 
1340.2%
 
2021-01-08T16:33:56.801013image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.2 KiB
0
14392 
1
 
728
ValueCountFrequency (%) 
01439295.2%
 
17284.8%
 
2021-01-08T16:33:56.865012image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.2 KiB
0
14463 
1
 
657
ValueCountFrequency (%) 
01446395.7%
 
16574.3%
 
2021-01-08T16:33:56.949014image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size118.2 KiB
0
14661 
1
 
459
ValueCountFrequency (%) 
01466197.0%
 
14593.0%
 
2021-01-08T16:33:57.011015image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Cover_Type
Real number (ℝ≥0)

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Memory size118.2 KiB
2021-01-08T16:33:57.112015image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median4
Q36
95-th percentile7
Maximum7
Range6
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.000066141
Coefficient of variation (CV)0.5000165352
Kurtosis-1.250016528
Mean4
Median Absolute Deviation (MAD)2
Skewness0
Sum60480
Variance4.000264568
MonotocityNot monotonic
2021-01-08T16:33:57.239600image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
7216014.3%
 
6216014.3%
 
5216014.3%
 
4216014.3%
 
3216014.3%
 
2216014.3%
 
1216014.3%
 
ValueCountFrequency (%) 
1216014.3%
 
2216014.3%
 
3216014.3%
 
4216014.3%
 
5216014.3%
 
6216014.3%
 
7216014.3%
 
ValueCountFrequency (%) 
7216014.3%
 
6216014.3%
 
5216014.3%
 
4216014.3%
 
3216014.3%
 
2216014.3%
 
1216014.3%
 

Interactions

2021-01-08T16:33:01.475761image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:02.037889image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:02.318889image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:02.648571image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:02.947564image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:03.199607image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:03.439451image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:03.775450image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:04.016449image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:04.241541image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:04.461257image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:04.719265image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:04.957875image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:05.185412image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:05.422409image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:05.744405image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:05.951662image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:06.198697image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:06.442698image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:06.821742image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:07.049814image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:07.372227image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:07.594332image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:07.855319image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:08.105319image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:08.389392image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:08.640521image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:08.866524image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:09.084532image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:09.323523image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:09.555520image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:09.791521image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:10.069521image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:10.376522image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:10.654521image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:10.905522image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:11.218523image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:11.487523image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:11.721525image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:11.984527image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:12.171520image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:12.393527image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:12.681527image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:12.990521image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:13.241521image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:13.464526image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:13.677536image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:13.937520image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:14.152522image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:14.400522image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:14.647521image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:14.844524image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:15.020523image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:15.220520image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:15.543521image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:15.740163image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:15.935680image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:16.148709image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:16.334681image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:16.545403image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:16.739404image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:16.929402image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:17.120971image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:17.316530image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:17.492532image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:17.678530image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:17.865612image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:18.079573image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:18.255573image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:18.448644image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:18.615646image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:18.821744image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:19.007716image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:19.233711image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:19.419195image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:19.619196image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:19.893285image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:20.188596image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:20.434109image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:20.684262image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:20.933279image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:21.333260image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:21.551264image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:21.801438image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:22.029446image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:22.256438image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:22.468441image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:22.684534image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:22.902529image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:23.123532image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:23.361693image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:23.581664image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:23.795289image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:24.037284image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:24.272285image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:24.539822image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:24.823345image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:25.289344image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:25.533348image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:25.805349image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:26.055343image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:26.329344image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:26.581403image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:26.828410image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:27.070552image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:27.351589image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:27.585588image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:27.854109image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:28.087697image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:28.315697image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:28.536700image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:28.799319image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:29.027321image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:29.251908image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:29.470898image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:29.712899image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:29.925923image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:30.202454image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:30.421451image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:30.655454image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:30.885451image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:31.142591image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:31.420736image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:31.683735image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:31.927738image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:32.186815image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:32.470816image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:32.716851image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:32.962940image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:33.210941image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:33.461085image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:33.705610image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:33.937246image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:34.184354image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:34.421353image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:34.644426image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:34.854488image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:35.098489image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:35.330491image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:35.568561image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:35.800561image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:36.036621image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:36.254622image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:36.500259image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Correlations

2021-01-08T16:33:57.641639image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2021-01-08T16:34:00.529377image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2021-01-08T16:34:03.723222image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2021-01-08T16:34:06.641693image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2021-01-08T16:33:37.428340image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-08T16:33:46.705870image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Sample

First rows

IdElevationAspectSlopeHorizontal_Distance_To_HydrologyVertical_Distance_To_HydrologyHorizontal_Distance_To_RoadwaysHillshade_9amHillshade_NoonHillshade_3pmHorizontal_Distance_To_Fire_PointsWilderness_Area1Wilderness_Area2Wilderness_Area3Wilderness_Area4Soil_Type1Soil_Type2Soil_Type3Soil_Type4Soil_Type5Soil_Type6Soil_Type7Soil_Type8Soil_Type9Soil_Type10Soil_Type11Soil_Type12Soil_Type13Soil_Type14Soil_Type15Soil_Type16Soil_Type17Soil_Type18Soil_Type19Soil_Type20Soil_Type21Soil_Type22Soil_Type23Soil_Type24Soil_Type25Soil_Type26Soil_Type27Soil_Type28Soil_Type29Soil_Type30Soil_Type31Soil_Type32Soil_Type33Soil_Type34Soil_Type35Soil_Type36Soil_Type37Soil_Type38Soil_Type39Soil_Type40Cover_Type
01259651325805102212321486279100000000000000000000000000000001000000000005
122590562212-63902202351516225100000000000000000000000000000001000000000005
23280413992686531802342381356121100000000000000100000000000000000000000000002
3427851551824211830902382381226211100000000000000000000000000000000100000000002
452595452153-13912202341506172100000000000000000000000000000001000000000005
5625791326300-15672302371406031100000000000000000000000000000001000000000002
67260645727056332222251386256100000000000000000000000000000001000000000005
78260549423475732222301446228100000000000000000000000000000001000000000005
892617459240566662232211336244100000000000000000000000000000001000000000005
91026125910247116362282191246230100000000000000000000000000000001000000000005

Last rows

IdElevationAspectSlopeHorizontal_Distance_To_HydrologyVertical_Distance_To_HydrologyHorizontal_Distance_To_RoadwaysHillshade_9amHillshade_NoonHillshade_3pmHorizontal_Distance_To_Fire_PointsWilderness_Area1Wilderness_Area2Wilderness_Area3Wilderness_Area4Soil_Type1Soil_Type2Soil_Type3Soil_Type4Soil_Type5Soil_Type6Soil_Type7Soil_Type8Soil_Type9Soil_Type10Soil_Type11Soil_Type12Soil_Type13Soil_Type14Soil_Type15Soil_Type16Soil_Type17Soil_Type18Soil_Type19Soil_Type20Soil_Type21Soil_Type22Soil_Type23Soil_Type24Soil_Type25Soil_Type26Soil_Type27Soil_Type28Soil_Type29Soil_Type30Soil_Type31Soil_Type32Soil_Type33Soil_Type34Soil_Type35Soil_Type36Soil_Type37Soil_Type38Soil_Type39Soil_Type40Cover_Type
151101511125083326671644204173911385001000000000010000000000000000000000000000006
1511115112261059176010674231202981328001000000000010000000000000000000000000000006
1511215113260038251240589212178891261001000000000010000000000000000000000000000006
151131511426881041544310805245219991266001000000000001000000000000000000000000000003
1511415115267010812624247302412251121231001000000000001000000000000000000000000000003
151151511626072432325876601702512141282001000010000000000000000000000000000000000003
1511615117260312119633195618249221911325001000010000000000000000000000000000000000003
1511715118249213425365117335250220831187001000010000000000000000000000000000000000003
1511815119248716728218101242229237119932001000010000000000000000000000000000000000003
151191512024751973431978270189244164914001001000000000000000000000000000000000000003